科研之友
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摘要
The interaction of drugs and non-therapeutic xenobiotics constitutes a central role in human health risk assessment. Still, available data are rare. Two different models have been established to predict mixture toxicity from single dose data, namely, the concentration addition (CA) and independent action (IA) model. However, chemicals can also act synergistic or antagonistic or in dose level deviation, or in a dose ratio dependent deviation. In the present study we used the MIXTOX model (EU project ENV4-CT97-0507), which incorporates these algorithms, to assess effects of the binary mixtures in the human hepatoma cell line HepG2. These cells possess a liver-like enzyme pattern and a variety of xenobiotic-metabolizing enzymes (phases I and II). We tested binary mixtures of the metal nickel, the anti-inflammatory drug diclofenac, and the antibiotic agent irgasan and compared the experimental data to the mathematical models. Cell viability was determined by three different methods the MTT-, AlamarBlue (R) and NRU assay. The compounds were tested separately and in combinations. We could show that the metal nickel is the dominant component in the mixture, affecting an antagonism at low-dose levels and a synergism at high-dose levels in combination with diclofenac or irgasan, when using the NRU and the AlamarBlue assay. The dose-response surface of irgasan and diclofenac indicated a concentration addition. The experimental data could be described by the algorithms with a regression of up to 90%, revealing the HepG2 cell line and the MIXTOX model as valuable tool for risk assessment of binary mixtures for cytotoxic endpoints. However the model failed to predict a specific mode of action, the CYP1A1 enzyme activity.
- 出版日期2010-5-1
